Pedestrian Detection in Crowded Environments through Bayesian Prediction of Sequential Probability Matrices
Javier Hernández‐Aceituno, Leopoldo Acosta, José D. Piñeiro · Journal of Sensors · 2015
In order to safely navigate populated environments, an autonomous vehicle must be able to detect human shapes using its sensory systems, so that it can properly avoid a collision. In this paper, we introduce a Bayesian approach to the Viola-Jones algorithm, as a method to automatically detect pedestrians in image sequences. We present a probabilistic interpretation of the basic execution of the original tool and develop a technique to produce approximate convolutions of probability matrices with multiple local maxima.